Instructions to use damgomz/fp_bs8_lr5e4_x2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use damgomz/fp_bs8_lr5e4_x2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="damgomz/fp_bs8_lr5e4_x2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("damgomz/fp_bs8_lr5e4_x2") model = AutoModelForMaskedLM.from_pretrained("damgomz/fp_bs8_lr5e4_x2") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
CHANGED
|
@@ -66,3 +66,4 @@ Epoch | Train Loss | Test Loss
|
|
| 66 |
| 0.0 | 14.495950 | 18.152991 |
|
| 67 |
| 0.5 | 7.178231 | 7.069824 |
|
| 68 |
| 1.0 | 7.041129 | 7.029052 |
|
|
|
|
|
|
| 66 |
| 0.0 | 14.495950 | 18.152991 |
|
| 67 |
| 0.5 | 7.178231 | 7.069824 |
|
| 68 |
| 1.0 | 7.041129 | 7.029052 |
|
| 69 |
+
| 1.5 | 7.012486 | 7.008510 |
|